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Dung’s argumentation frameworks are adopted in a variety of applications, from\ud argument-mining, to intelligence analysis and legal reasoning. Despite this broad spectrum\ud of already existing applications, the mostly adopted solver—in virtue of its\ud simplicity—is far from being comparable to the current state-of-the-art solvers. On the\ud other hand, most of the current state-of-the-art solvers are far too complicated to be\ud deployed in real-world settings. In this paper we provide and extensive description of\ud jArgSemSAT, a Java re-implementation of ArgSemSAT. ArgSemSAT represents the best\ud single solver for argumentation semantics with the highest level of computational complexity.\ud We show that jArgSemSAT can be easily integrated in existing argumentation\ud systems (1) as an off-the-shelf, standalone, library; (2) as a Tweety compatible library;\ud and (3) as a fast and robust web service freely available on the Web. Our large experimental\ud analysis shows that—despite being written in Java—jArgSemSAT would have\ud scored in most of the cases among the three bests solvers for the two semantics with\ud highest computational complexity—Stable and Preferred—in the last competition on\ud computational models of argumentation.

This work provides initial results on the relationship between argumentation and Paul Thagard’s coherence theory. We study the relationship, via appropriate transformations, between different types of coherent graphs (according to the values in the arcs) and different argumentation frameworks such as Dung’s abstract argumentation framework, weighted argument systems or preference-based argumentation. The practical interest of our study is to show that coherence theory and argumentation can be mutually useful. © Springer International Publishing AG 2017. 10207 LNAI 565 579 Sponsors: Conference code: 193709

Agents disagree in many situations and in many ways on their beliefs, preferences and goals. Abstract argumentation frameworks are a formal model to handle disagreement, which is represented as a conflict relation between a set of arguments. To solve the conflict and identify justified arguments, a single argumentation semantics is applied at a global level, under the assumption that the involved conflicts are essentially homogeneous. In the talk I will argue that disagreements are in general heterogeneous and thus should be treated in different ways according both to their nature and to the specific agents features. Accordingly, a general model of abstract argumentation will be discussed, able to handle heterogeneous disagreements by means of multiple argumentation semantics at a local level.

Das Forschungsgebiet der Argumentation, inbesonders formale Modelle von Argumentation, wurde in letzter Zeit zu einem wichtigen Thema in der k��nstlichen Intelligenz. Dies ergibt sich durch die Verbindung zu - sowie diversen Anwendungen in - anderen Disziplinen wie Philosophie, Rechtswissenschaften, Logik, und Medizin, aber auch durch die thematische N��he zu anderen Formlismen der KI, insbesonders aus dem Bereich der Wissensrepr��sentation. Obwohl eine Vielzahl von Formalismen f��r Argumentation vorgeschlagen wurde, sticht ein Ansatz hervor, n��mlich die von Dung eingef��hrten abstrakten Argumentation Frameworks (AFs). Ein AF ist einfach ein gerichteter Graph, wobei die Knoten Argumente repr��sentieren, und die Kanten Konflikte. Diese Konflikte werden dann mittels Semantiken aufgel��st. Obwohl AFs sehr popul��r sind, st����t ihre Aussdrucksst��rke in verschiedenen Anwendungen an ihre Grenzen. Daher finden sich in der Literatur zahlreiche Erweiterungen, wobei Abstract Dialectical Frameworks (ADFs) weit verbreitet sind. ADFs erlauben flexible Beziehungen zwischen Argumenten, welche mittles aussagenlogischer Formalen spezifiziert werden. In dieser Arbeit wollen wir einige L��cken in der Forschung ��ber ADFs schlie��en. So werden wir z.B. das Fundamentale Lemma von Dung auf ADFs erweitern. Weiters wollen wir untersuchen, ob sich gewisse Eigenschaften, die f��r spezielle Subklassen von AFs gelten, sich mittels geeigneter Definition von Subklassen auf ADFs ubertragen. Hierf��r definieren wir verschiedene neue Klassen (symmetric ADFs, acyclic ADFs, attack symmetric ADFs, acyclic support ADFs, complete ADFs) und untersuchen deren Eigenschaften. Ein weiterer Aspekt dieser Arbeit sind Resultate zur Aussdrucksst��rke dieser Klassen in bezug auf das Konzept der sogenannten Realisierbarkeit. Abschlie��end stellen wir eine Implementierung eines Generators f��r die genannten ADF Subklassen vor und untersuchen damit inwiefern sich existierende Systeme f��r ADFs in der Handhabung von Zyklen verhalten., Argumentation, and in particular computational models of argumentation, has recently become a main topic within artificial intelligence. This is not only because of its crucial importance and wide applications in other fields of science like philosophy, law, logic, and medicine but also because of its connection to other areas of AI, in specific, knowledge representation. Although there exists a wide variety of formalisms of argumentation, one popular, prominent and simple formalism stands out, namely abstract argumentation frameworks (AFs) first introduced by Dung. Intuitively, an AF is a directed graph in which nodes represent arguments and directed links represent conflicts between arguments. The conflicts between the arguments are resolved on the semantical level. Although AFs are very popular tools in argumentation because of their conceptual simplicity, they are not expressive enough to define different kind of relations. Several generalizations of AFs exist, in particular, abstract dialectical frameworks (ADFs), a powerful generalization of AFs, are widely studied. ADFs, first defined by Brewka and Woltran, are capable to express arbitrary relations between arguments with no need of defining a new type of relations and by assigning an acceptance condition to each argument in the form of a propositional formula. In the current work we close some gaps in existing research on ADFs. More specifically, we investigate whether some main results carry over from AFs to ADFs. For instance, we reformulate Dung���s Fundamental Lemma and we study under which conditions all semantics of an ADF coincide. We also study whether particular properties which are known to hold for certain subclasses can be extended to the world of ADFs by defining related subclasses of ADFs. To do so, we introduce several such classes (symmetric ADFs, acyclic ADFs, attack symmetric ADFs, acyclic support symmetric ADFs, complete ADFs) and investigate their properties. A central aspect of our work is comparing the expressivity of subclasses of AFs and ADFs from the perspective of realizability. At the end we introduce an implementation of a generator to produce such subclasses of ADFs. We use this generator in order to evaluate the effect of cycles on the performance of existing solvers for ADFs.

An intelligent agent may in general pursue multiple goals at the same time, which leads to arise some conflict among them. In this paper, we focus on these conflicts or incompatibilities among goals. Our approach is based on the model of Castelfranchi and Paglieri, in which, three forms of incompatibility and the criteria for selection of goals are defined. We characterise computationally the different forms of incompatibility (terminal, instrumental and superfluity) and propose a way, based on abstract argumentation theory, for selecting those goals that will continue to be pursued., Authors acknowledge the support of CAPES (Coordena¸c˜ao de Aperfei¸coamento de Pessoal de N´ıvel Superior) and CNPQ (National Counsel of Technological and Scientific Development) and the partial support of CSIC Intramural projects SMA (201550E040) and AMIDA (201450E009), the Spanish MICINN projects EdeTRI (TIN2012-39348-C02-01) and MILESS (TIN2013-45039-P), and the grants 2014-SGR-118 from the Generalitat de Catalunya.

In recent years the research field of argumentation has become a major topic in the study of artificial intelligence (AI). This is not only due to recent applications such as legal reasoning and medicine, but also because of fundamental connections to other areas of AI research such as nonmonotonic reasoning. AI and automated reasoning can be helpful to various tasks within the argumentation process, but the focus of this work is on the evaluation of the acceptability of conflicting arguments. The most prominent approach to this problem is the formal model of abstract argumentation frameworks (AFs) introduced by Dung. An AF is a directed graph where nodes represent arguments and directed edges represent conflicts between arguments. Conditions for the acceptability of arguments are given by argumentation semantics. Several semantics have been defined over the years. The central question, given an AF, is which sets of arguments (so-called extensions) can be jointly accepted under a certain semantics. While Dung��s argumentation frameworks enjoyed and still enjoy great popularity, their conceptual simplicity also imposes certain limitations, which has led to a considerable number of generalizations of Dung's AFs. In particular, abstract dialectical frameworks (ADFs) constitute a very powerful generalization of AFs by additionally assigning to each argument an acceptance condition in the form of a propositional formula. In this work we contribute to the advancement of the study of abstract argumentation by addressing aspects of expressiveness and dynamics of argumentation semantics in AFs as well as in ADFs. In terms of expressiveness we first complement recent work on realizability in AFs. Moreover, we investigate the role of arguments that do not appear in any extension, so-called rejected arguments, and study the induced class of compact argumentation frameworks. We give full pictures of the relations between the compact AF classes and between the expressiveness of the various semantics when restricted to compact AFs. Then, we lift the study of expressiveness to the concept of input-output AFs and give, for the major semantics, exact characterizations of functions which are realizable in this setting. Finally, we present a unifying algorithmic approach to realizability capturing AFs and ADFs as well as intermediate formalisms in a modular way, which is also implemented in answer set programming. These results not only contribute to the systematic comparison of semantics, but can also provide the theoretical basis for the advancement of solving techniques for problems in argumentation. Taking into account the dynamic nature of argumentation, we study two central issues therein: revision and splitting. For revision we apply the seminal AGM theory of belief change to argumentation. We are the first to present a representation theorem for revision operators which guarantee to result in a single framework. For AFs we give a generic solution which applies to many prominent semantics. For ADFs we study revision under preferred and admissible semantics as well as a novel hybrid approach. We also present concrete belief change operators and analyze their computational complexity. Finally, we study splitting of ADFs, aiming for optimization of computation by incremental computation of semantics. We provide suitable techniques for directional splitting under all standard semantics of ADFs as well as for general splitting under selected semantics.

In the last decades, most works in the literature have been devoted to study argumentation formalisms that focus on a defeat relation among arguments. Recently, the study of a support relation between arguments regained attention among researchers; the bulk of the research has been centered on the study of support within the context of abstract argumentation by considering support as an explicit interaction between arguments. However, there exist other approaches that take support into account in a different setting. This article surveys several interpretations of the notion of support as proposed in the literature, such as deductive support, necessary support, evidential support, subargument, and backing, among others. The aim is to provide a comprehensive study where similarities and differences among these interpretations are highlighted, as well as discuss how they are addressed by different argumentation formalisms. Fil: Cohen, Andrea. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computacion; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Gottifredi, Sebastián. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computacion; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: García, Alejandro Javier. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computacion; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Simari, Guillermo Ricardo. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computacion; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Arguments need to be judged against other arguments. The decision to accept or reject an argument is generally a global decision that involves examining the same question for other arguments that oppose or can defend the argument in question. This article presents the acceptability semantics for abstract argumentation that through a recursive definition gives a global assignment of the acceptable and non-acceptable subsets of arguments. This semantics stems from the aim to formalize directly the generally accepted intuition that: 'An argument can be accepted if and only if all its challenging arguments can be rejected.' The acceptability semantics tightly integrates the notion of defending against a challenging argument by counter-attacking it with the notion of self-defeating (or self-rejecting) arguments that (help to) bring about their own non-acceptability. The proposal is motivated by earlier studies of the semantics of Logic Programming (LP) in terms of argumentation, where the basic well founded and stable model semantics of LP can be uniformly captured using a recursively defined argumentation semantics for Negation as Failure and where these standard semantics of LP can be further extended through argumentation. © The Author, 2012. Published by Oxford University Press. All rights reserved. 23 5 991 1015 Cited By :5

Given a semantics σ, two argumentation frameworks (AFs) F and G are said to be standard equivalent if they possess the same extensions and strongly equivalent if, for any AF H, F conjoined with H and G conjoined with H are standard equivalent. Argumentation is a dynamic process and, in general, new arguments occur in response to a former argument or, more precisely, attack a former argument. For this reason, rather than considering arbitrary expansions we focus here on expansions where new arguments and attacks may be added but the attacks among the old arguments remain unchanged. We define and characterize two new notions of equivalence between AFs (which lie in-between standard and strong equivalence), namely normal and strong expansion equivalence. Furthermore, using the characterization theorems proved in this paper, we draw the connections between all mentioned notions of equivalence including further equivalence relations, so-called weak and local expansion equivalence.

International audience; Properties of argumentation semantics have been widely studied in the last decades. However, there has been no investigation on the question of difference measures between semantics. Such measures turn helpful when the semantics associated to an argumentation framework may have to be changed, in a way that ensures that the new semantics is not too dissimilar from the old one. Three main notions of difference measures between semantics are defined in this paper. Some of these measures are shown to be distances or semi-distances.

Case-based reasoning (CBR) is extensively used in AI in support of several applications, to assess a new situation (or case) by recollecting past situations (or cases) and employing the ones most similar to the new situation to give the assessment. In this paper we study properties of a recently proposed method for CBR, based on instantiated Abstract Argumentation and referred to as AA-CBR, for problems where cases are represented by abstract factors and (positive or negative) outcomes, and an outcome for a new case, represented by abstract factors, needs to be established. In addition, we study properties of explanations in AA-CBR and define a new notion of lean explanations that utilize solely relevant cases. Both forms of explanations can be seen as dialogical processes between a proponent and an opponent, with the burden of proof falling on the proponent.

In this paper we investigate the impact of automated configuration techniques on the ArgSemSAT solver—runner-up of the ICCMA 2015—for solving the enumeration of preferred extensions. Moreover, we introduce a fully automated method for varying how argumentation frameworks are represented in the input file, and evaluate how the joint configuration of frameworks and ArgSemSAT parameters can have a remarkable impact on performance. Our findings suggest that automated configuration techniques lead to improved performances in argumentation solvers, an important message for participants to the forthcoming competition.

We evaluate the state of the art of solvers for hard argumentation problems—the enumeration of preferred and stable extensions—to envisage future trends based on evidence collected as part of an extensive empirical evaluation. In the last international competition on computational models of argumentation a general impression was that reduction-based systems (either SAT-based or ASP-based) are the most efficient.\ud Our investigation shows that this impression is not true in full generality and suggests the areas where the relatively under-developed non reduction-based systems should focus more to improve their performance. Moreover, it also highlights that the state-of-the-art solvers are very complementary and can be successfully combined in portfolios: our best per-instance portfolio is 51% (resp. 53%) faster than the best single solver for enumerating preferred (resp. stable) extensions.

An Abstract Argumentation Framework AAF represents a useful technique for the analysis of arguments supporting or discouraging decisions i.e., information can be in conflict. In particular, we apply Abstract Argumentation to support the administration of security in computer networks. Our approach captures the high-level topology of a system and helps to specify which and where security countermeasures are more appropriate. We design a quantitative analysis on AAFs modelling our domain knowledge with the purpose to compare different decisions and select the most suitable one to protect the critical assets.

Abstract argumentation frameworks have received a lot of interest in recent years. Most computational problems in this area are intractable but several tractable fragments have been identified. In particular, Dunne showed that many problems can be solved in linear time for argumentation frameworks of bounded tree-width. However, these tractability results, which were obtained via Courcelleʼs Theorem, do not directly lead to efficient algorithms. The goal of this paper is to turn the theoretical tractability results into efficient algorithms and to explore the potential of directed notions of tree-width for defining larger tractable fragments. As a by-product, we will sharpen some known complexity results.

In this paper we investigate the use of classical logic as a basis for instantiating abstract argumentation frameworks. In the first part, we propose desirable properties of attack relations in the form of postulates and classify several well-known attack relations from the literature with regards to the satisfaction of these postulates. Furthermore, we provide additional postulates that help us prove characterisation results for these attack relations. In the second part of the paper, we present postulates regarding the logical content of extensions of argument graphs that may be constructed with classical logic. We then conduct a comprehensive study of the status of these postulates in the context of the various combinations of attack relations and extension semantics.

This thesis tackles the problem of integrating a new piece of information in an abstract argumenta- tion framework. Such a framework is a directed graph such that its nodes represent the arguments, and the directed edges represent the attacks between arguments. There are different ways to decide which arguments are accepted by the agent who uses such a framework to represent her beliefs.An agent may be confronted with a piece of information such that "this argument should be accepted", which is in contradiction with her current beliefs, represented by her argumentation framework.In this thesis, we have studied several approaches to incorporate a piece of information in an argumenta- tion framework.Our first contribution is an adaptation of the AGM framework for belief revision, which has been de- veloped for characterizing the incorporation of a new piece of information when the agent’s beliefs are represented in a logical setting. We have adapted the rationality postulates from the AGM framework to characterize the revision operators suited to argumentation frameworks, and we have identified several ways to generate the argumentation frameworks resulting from the revision.We have also shown how to use AGM revision as a tool for revising argumentation frameworks. Our approach uses a logical encoding of the argumentation framework to take advantage of the classical re- vision operators, for deriving the expected result.At last, we have studied the problem of enforcing a set of arguments (how to change an argumentation framework so that a given set of arguments becomes an extension). We have developed a new family of operators which guarantee the success of the enforcement process, contrary to the existing approaches, and we have shown that a translation of our approaches into satisfaction and optimization problems makes possible to develop efficient tools for computing the result of the enforcement.; Cette thèse traite du problème de l’intégration d’une nouvelle information dans un système d’argumen- tation abstrait. Un tel système est un graphe orienté dont les nœuds représentent les arguments, et les arcs représentent les attaques entre arguments. Il existe divers moyen de décider quels arguments sont acceptés par l’agent qui utilise un tel système pour représenter ses croyances.Il peut arriver dans la vie d’un agent qu’il soit confronté à une information du type "tel argument devrait être accepté", alors que c’est en contradiction avec ses croyances actuelles, représentées par son système d’argumentation.Nous avons étudié dans cette thèse diverses approches pour intégrer une information à un système d’ar- gumentation.Notre première contribution est une adaptation du cadre AGM pour la révision de croyances, habituelle- ment utilisé lorsque les croyances de l’agent sont représentées dans un formalisme logique. Nous avons notamment adapté les postulats de rationalité proposés dans le cadre AGM pour pouvoir caractériser des opérateurs de révision de systèmes d’argumentation, et nous avons proposé différents moyens de générer les systèmes d’argumentation résultant de la révision.Nous avons ensuite proposé d’utiliser la révision AGM comme un outil pour réviser les systèmes d’ar- gumentation. Il s’agit cette fois-ci d’une approche par encodage en logique du système d’argumentation, qui permet d’utiliser les opérateurs de révision usuels pour obtenir le résultat souhaité.Enfin, nous avons étudié le problème du forçage d’un ensemble d’arguments (comment modifier le sys- tème pour qu’un ensemble donné soit une extension). Nous avons proposé une nouvelle famille d’opé- rateurs qui garantissent le succès de l’opération, contrairement aux opérateurs de forçage existants, et nous avons montré qu’une traduction de nos approches en problèmes de satisfaction ou d’optimisation booléenne permet de développer des outils efficaces pour calculer le résultat du forçage.

24th International Joint Conferences on Artificial Intelligence (IJCAI 2015); International audience; In the context of bipolar argumentation (argumentation with two kinds of interaction, attacks and supports), we present an axiomatic approach for taking into account a special interpretation of the support relation, the necessary support. We propose constraints that should be imposed to a bipolar argumentation system using this interpretation. Some of these constraints concern the new attack relations, others concern acceptability. We extend basic Dung's framework in different ways in order to propose frameworks suitable for encoding these constraints. By the way, we propose a formal study of properties of necessary support.

Formal argumentation is a popular reasoning method in knowledge representation for intelligent systems. For the past 20 years it has been based on Dung’s abstract argumentation theory. More recently several challenges have been made to this standard - for example in dynamics and aggregation of argumentation frameworks. To support these new developments in this thesis new foundations are developed based on distance measures. We introduce postulates for distance measures and we show their consistency by constructing concrete measures. In the process we develop the new notion of issue. Subsequently we use the distance measures in argumentation using distance based operators introduced by Miller and Osherson in judgment aggregation. Moreover in this thesis we also improve dialectical proof procedures for grounded semantics and study postulates of non-interference and crash resistance for Dung based non-monotonic inference.

Argumentation has been proved as a simple yet powerful approach to manage conflicts in reasoning with the purpose to find subsets of “surviving” arguments. Our intent is to exploit such form of resolution to support the administration of security in complex systems, e.g., in case threat countermeasures are in conflict with non-functional requirements. The proposed formalisation is able to find the required security controls and explicitly provide arguments supporting this selection. Therefore, an explanation automatically comes as part of the suggested solution, facilitating human comprehension.

This thesis tackles the problem of integrating a new piece of information in an abstract argumenta- tion framework. Such a framework is a directed graph such that its nodes represent the arguments, and the directed edges represent the attacks between arguments. There are different ways to decide which arguments are accepted by the agent who uses such a framework to represent her beliefs.An agent may be confronted with a piece of information such that "this argument should be accepted", which is in contradiction with her current beliefs, represented by her argumentation framework.In this thesis, we have studied several approaches to incorporate a piece of information in an argumenta- tion framework.Our first contribution is an adaptation of the AGM framework for belief revision, which has been de- veloped for characterizing the incorporation of a new piece of information when the agent’s beliefs are represented in a logical setting. We have adapted the rationality postulates from the AGM framework to characterize the revision operators suited to argumentation frameworks, and we have identified several ways to generate the argumentation frameworks resulting from the revision.We have also shown how to use AGM revision as a tool for revising argumentation frameworks. Our approach uses a logical encoding of the argumentation framework to take advantage of the classical re- vision operators, for deriving the expected result.At last, we have studied the problem of enforcing a set of arguments (how to change an argumentation framework so that a given set of arguments becomes an extension). We have developed a new family of operators which guarantee the success of the enforcement process, contrary to the existing approaches, and we have shown that a translation of our approaches into satisfaction and optimization problems makes possible to develop efficient tools for computing the result of the enforcement., Cette thèse traite du problème de l’intégration d’une nouvelle information dans un système d’argumen- tation abstrait. Un tel système est un graphe orienté dont les nœuds représentent les arguments, et les arcs représentent les attaques entre arguments. Il existe divers moyen de décider quels arguments sont acceptés par l’agent qui utilise un tel système pour représenter ses croyances.Il peut arriver dans la vie d’un agent qu’il soit confronté à une information du type "tel argument devrait être accepté", alors que c’est en contradiction avec ses croyances actuelles, représentées par son système d’argumentation.Nous avons étudié dans cette thèse diverses approches pour intégrer une information à un système d’ar- gumentation.Notre première contribution est une adaptation du cadre AGM pour la révision de croyances, habituelle- ment utilisé lorsque les croyances de l’agent sont représentées dans un formalisme logique. Nous avons notamment adapté les postulats de rationalité proposés dans le cadre AGM pour pouvoir caractériser des opérateurs de révision de systèmes d’argumentation, et nous avons proposé différents moyens de générer les systèmes d’argumentation résultant de la révision.Nous avons ensuite proposé d’utiliser la révision AGM comme un outil pour réviser les systèmes d’ar- gumentation. Il s’agit cette fois-ci d’une approche par encodage en logique du système d’argumentation, qui permet d’utiliser les opérateurs de révision usuels pour obtenir le résultat souhaité.Enfin, nous avons étudié le problème du forçage d’un ensemble d’arguments (comment modifier le sys- tème pour qu’un ensemble donné soit une extension). Nous avons proposé une nouvelle famille d’opé- rateurs qui garantissent le succès de l’opération, contrairement aux opérateurs de forçage existants, et nous avons montré qu’une traduction de nos approches en problèmes de satisfaction ou d’optimisation booléenne permet de développer des outils efficaces pour calculer le résultat du forçage.

In this paper we explore how the seminal Dung’s abstract argumentation framework can be extended to handle arguments containing gradual concepts. We allow arguments to have a degree of truth associated with them and we investigate the degree of truth to which each argument can be considered accepted, rejected and undecided by an abstract argumentation semantics. We propose a truth-compositional recursive computation, and we discuss examples using the major multi-valued logics such as Godel’s, Zadeh’s and Łukasiewicz's logic. The findings are a contribution in the field of non-monotonic approximate reasoning and they also represent a well-grounded proposal towards the introduction of gradualism in argumentation systems.

In large industries usage of advanced technological methods and modern equipment comes with the problem of storing, interpreting and analyzing huge amount of information. Typical sources for this data include a myriad of sensors mounted at the industrial machinery, measuring qualities such as temperatures, movement and vibration, pressure, and many more. However, these sensors are complex technical devices, which means that they can fail and their readings can become unreliable, or -dirty-. Low quality data makes it hard to solve the original task of assessing system and process status and controlling the system behavior. So, data quality is one of the major challenges considering a rapid growth of information, fragmentation of information systems, incorrect data formatting and other issues. The aim of this thesis is to propose a novel approach to address data quality issues in industrial datasets, in particular, measurements of sensors mounted at power generation facilities. The most common approach to detect anomalies in data is the analysis by means of the statistical and machine learning techniques. However, analyzing data alone can not always give satisfactory results. For instance, suspicious sensor readings may not indicate at bad quality of data, but at an appliance functioning abnormality detected by this sensor. Therefore, we propose to use additional available information on the domain. The approach presented in this work brings together several well-known techniques, which come from the worlds of computational logic and statistics, improving the results of data quality assessment and improvement procedure. The application domain and the dependencies between its objects are represented as a knowledge-based model, while statistics identifies data anomalies, such as outlying or missing values, in sensor measurement data. In this work we represent domain knowledge in OWL ontology, which covers the topology of an industrial equipment and an information about measuring devices installed. Providing statistical computations with the additional information from the model allows to validate and improve the results. Thus, comparing and analyzing readings provided by sensors of the same type and mounted at the same component of an appliance helps to identify possibly damaged sensors, as well as to distinguish between data quality inconsistencies found in single sensor readings from anomalies in machinery functioning detected by other measuring devices. Based on the proposed approach a software demonstrator has been implemented and tested, proving that the usage of the additional information provided by the semantic model improves the results of statistical analysis.

International audience; We study the computational complexity of problems that arise in abstract argumentation in the context of dynamic argumentation, minimal change, and aggregation. In particular, we consider the following problems where always an argumentation framework F and a small positive integer k are given. The Repair problem asks whether a given set of arguments can be modified into an extension by at most k elementary changes (i.e., the extension is of distance k from the given set). The Adjust problem asks whether a given extension can be modified by at most k elementary changes into an extension that contains a specified argument. The Center problem asks whether, given two extensions of distance k, whether there is a “center” extension that is of distance at most k − 1 from both given extensions.We study these problems in the framework of parameterized complexity, and take the distance k as the parameter. Our results cover several different semantics, including admissible, complete, preferred, semi-stable and stable semantics.

We propose and investigate a simple ranking-measure-based extension semantics for abstract argumentation frameworks based on their generic instantiation by default knowledge bases and the ranking construction semantics for default reasoning. In this context, we consider the path from structured to logical to shallow semantic instantiations. The resulting well-justified JZ-extension semantics diverges from more traditional approaches., Proceedings of the 15th International Workshop on Non-Monotonic Reasoning (NMR 2014). This is an improved and extended version of the author's ECSQARU 2013 paper

This work explores the revival of arguments in abstract argumentation theory. A revived argument is an argument that is put forward in a specific context, but is somehow put aside because it did not seem relevant to the discussion or it has been denied, and then becomes useful in another context when a similar argument emerges. We obtain necessary conditions for argument revival using real-world examples and show that a recently proposed temporal argumentation framework cannot account for argument revival. Next, we propose an algorithm for argument revival that uses arguments annotated by a context label. This algorithm determines what arguments can be revived using the context neighborhood, the attack relations and a revival policy.

In this paper we show how to argue about agreements based on de- pendence. First, we introduce a formal theory of arguing about agreements by instantiating Dung’s abstract theory of argumentation with proposals for agree- ments represented as dependence networks. Second, we show that acceptable agreements are exchange based—satisfying the so-called do-ut-des principle— and not redundant. Third, to further decrease the number of proposals, we define a notion of minimal proposals. Roughly, all proposals can be split into a number of minimal sub-proposals such that if the proposal is acceptable, then its minimal sub-proposals are acceptable too. We show that minimal proposals satisfy the indecomposable do-ut-des property, i.e., they cannot be split into two nonempty sub-proposals with at most one shared agent.

The concept of explanation has received attention from different areas in Computer Science, particularly in the knowledge-based systems and expert systems communities. At the same time, argumentation has evolved as a new paradigm for conceptualizing commonsense reasoning, resulting in the formalization of different argumentation frameworks and the development of several real-world argument-based applications. Although the notions of explanation and argument for a claim share many common elements in knowledge-based systems their interrelationships have not yet been formally studied in the context of the current argumentation research in Artificial Intelligence. This article explores these ideas by providing a new perspective on how to formalize dialectical explanation support for argument-based reasoning. To do this, we propose a formalization of explanations for abstract argumentation frameworks with dialectical constraints where different emerging properties are studied and analyzed. As a concrete example of the formalism introduced we show how it can be fleshed out in an implemented rule-based argumentation system. Fil: García, Alejandro Javier. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina Fil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina Fil: Rotstein, Nicolas Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina Fil: Simari, Guillermo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina

This paper presents an overview on the state of the art of semantics for abstract argumentation, covering both some of the most influential literature proposals and some general issues concerning semantics definition and evaluation. As to the former point, the paper reviews Dung's original notions of complete, grounded, preferred, and stable semantics, as well as subsequently proposed notions like semi-stable, ideal, stage, and CF2 semantics, considering both the extension-based and the labelling-based approaches with respect to their definitions. As to the latter point, the paper presents an extensive set of general properties for semantics evaluation and analyzes the notions of argument justification and skepticism. The final part of the paper is focused on the discussion of some relationships between semantics properties and domain-specific requirements.

The study of arguments as abstract entities and their interaction as introduced by Dung (Artificial Intelligence 177, 1995) has become one of the most active research branches within Artificial Intelligence and Reasoning. A main issue for abstract argumentation systems is the selection of acceptable sets of arguments. Value-based argumentation, as introduced by Bench-Capon (J. Logic Comput. 13, 2003), extends Dung's framework. It takes into account the relative strength of arguments with respect to some ranking representing an audience: an argument is subjectively accepted if it is accepted with respect to some audience, it is objectively accepted if it is accepted with respect to all audiences. Deciding whether an argument is subjectively or objectively accepted, respectively, are computationally intractable problems. In fact, the problems remain intractable under structural restrictions that render the main computational problems for non-value-based argumentation systems tractable. In this paper we identify nontrivial classes of value-based argumentation systems for which the acceptance problems are polynomial-time tractable. The classes are defined by means of structural restrictions in terms of the underlying graphical structure of the value-based system. Furthermore we show that the acceptance problems are intractable for two classes of value-based systems that where conjectured to be tractable by Dunne (Artificial Intelligence 171, 2007).

In this paper we conceptualize abstract argumentation in terms of successful and unsuccessful attacks, such that arguments are accepted when there are no successful attacks on them. We characterize the relation between attack semantics and Dung’s approach, and we define an SCC recursive algorithm for attack semantics using attack labelings.

Argumentation has been acknowledged as a powerful mechanism for automated decision making. In this context several recent works have studied the problem of accommodating preference information in argumentation. The majority of these studies rely on Dung's abstract argumentation framework and its underlying acceptability semantics. In this paper we show that Dung's acceptability semantics, when applied to a preference-based argumentation framework for decision making purposes, may lead to counter intuitive results, as it does not take appropriately into account the preference information. To remedy this we propose a new acceptability semantics, called super-stable extension semantics, and present some of its properties. Moreover, we show that argumentation can be understood as a multiple criteria decision problem, making in this way results from decision theory applicable to argumentation. © 2009 Springer-Verlag Berlin Heidelberg. 5783 LNAI 225 236 Sponsors: DIMACS DAUPHINE UNIVERSITE PARIS CNRS COST EUROPEAN SCIENCE FOUNDATION Conference code: 77991 Cited By :11

In the current paper, we re-examine how abstract argumentation can be formulated in terms of labellings, and how the resulting theory can be applied in the field of modal logic. In particular, we are able to express the (complete) extensions of an argumentation framework as models of a set of modal logic formulas that represents the argumentation framework. Using this approach, it becomes possible to define the grounded extension in terms of modal logic entailment.

An abstract argument system or argumentation framework, as introduced in a seminal paper by Dung [13], is simply a pair 〈A ,R〉 consisting of a set A whose elements are called arguments and of a binary relation R on A called attack relation. The set A may be finite or infinite in general, however, given the introductory purpose of this chapter, we will restrict the presentation to the case of finite sets of arguments. An argumentation framework has an obvious representation as a directed graph where nodes are arguments and edges are drawn from attacking to attacked arguments. A simple example of argumentation framework AF1 = 〈{a,b},{(b,a)}〉 is shown in Figure 1. While the word argument may recall several intuitive meanings, like the ones of “line of reasoning leading from some premise to a conclusion” or of “utterance in a dispute”, abstract argument systems are not (even implicitly or indirectly) bound to any of them: an abstract argument is not assumed to have any specific structure but, roughly speaking, an argument is anything that may attack or be attacked by another argument. Accordingly, the argumentation framework depicted in Figure 1 is suitable to represent many different situations. For instance, in a context of reasoning about weather, argument a may be associated with the inferential step

Within the last decade, abstract argumentation has emerged as a central field in Artificial Intelligence. Besides providing a core formalism for many advanced argumentation systems, abstract argumentation has also served to capture several non-monotonic logics and other AI related principles. Although the idea of abstract argumentation is appealingly simple, several reasoning problems in this formalism exhibit high computational complexity. This calls for advanced techniques when it comes to implementation issues, a challenge which has been recently faced from different angles. In this survey, we give an overview on different methods for solving reasoning problems in abstract argumentation and compare their particular features. Moreover, we highlight available state-of-the-art systems for abstract argumentation, which put these methods to practice.